Some telecommunications network elements have distributed internal processing architectures. For example, the Eagle® signal transfer point (STP) and IP7 Secure Gateway™ products available from Tekelec of Calabasas, Calif., are two examples of such distributed processing systems. FIG. 1 is block diagram, which illustrates the distributed system architecture of a Tekelec Eagle® STP 100. In FIG. 1, STP 100 includes an interprocessor message transport (IMT) communication bus 102, multiple signaling system 7 (SS7) link interface communication modules (LIMs) 104, and multiple uniformly provisioned, database service modules (DSMs) 106. In this example, DSMs 106 are provisioned to support local number portability (LNP) processing of received signaling messages. Each of the DSMs of cluster 106 is provisioned with the same LNP translation data. Received signaling messages that require LNP translation processing are load-shared among DSMs of cluster 106. As indicated in FIG. 1, each DSM of cluster 106 contains a complete copy of all LNP translation data, which is obtained from a local provisioning system that includes a local service management system (LSMS) 110 and one or more Eagle® LNP application processor (ELAP) provisioning servers 112.
In the exemplary STP architecture shown in FIG. 1, a signaling message requiring LNP translation service is received by a LIM and is distributed to an available LNP DSM of cluster 106. Such a system architecture is attractive because a minimal message processing burden is placed on the LIM communication modules, and consequently, high message throughput rates may be achieved. However, recent developments in the telecommunications industry have exposed a potential weakness or shortcoming in storing all of the LNP data in a single database. This shortcoming involves cost and processing inefficiencies that emerge when the amount of number portability data that must be stored and accessed on each DSM becomes great. For example, the time required to perform each lookup in the database increases as the size of the database increases. In addition, storing multiple copies of a large database unnecessarily wastes memory and card reload times will increase proportionally to the increase in database size.
Accordingly, there exists a need for improved methods and systems for storing and accessing large message processing data sets in a signaling message routing node.